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Detection of Multilayer Cirrus Cloud Systems Using AVHRR Data: Verification Based on FIRE II IFO Composite Measurements

S. C. OuDepartment of Meteorology/CARSS, University of Utah, Salt Lake City, Utah

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K. N. LiouAtmospheric Sciences Division, NASA/Langley Research Center, Hampton, Virginia

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B. A. BaumAtmospheric Sciences Division, NASA/Langley Research Center, Hampton, Virginia

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Abstract

A numerical scheme has been developed to identify multilayer cirrus cloud systems using Advanced Very Higher Resolution Radiometer (AVHRR) data. It is based on the physical properties of the AVHRR channels 1–2 reflectance ratios, the brightness temperature differences between channels 4 and 5, and the channel 4 brightness temperatures. In this scheme, clear pixels are first separated from cloudy pixels, which are then classified into three types: cirrus, cirrus/low cloud, and low clouds. The authors have applied this scheme to the satellite data collected over the FIRE II IFO [First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment II intensive field observations area during nine overseas within seven observation dates. Determination of the threshold values used in the detection scheme are based on statistical analysts of these satellite data. The authors have validated the detection results against the cloudy conditions inferred from the collocated and coincident ground-based lidar and radar images, balloonborne replicator data, and National Center for Atmospheric Research CLASS (Cross-chain Loran Atmospheric Sounding System) humidity soundings on a case-by-case basis. In every case, the satellite detection results are consistent with the cloudy conditions inferred from these independent and complementary measurement. The present scheme is well suited for the detection of midlatitude, multilayer cirrus cloud systems and tropical anvils.

Abstract

A numerical scheme has been developed to identify multilayer cirrus cloud systems using Advanced Very Higher Resolution Radiometer (AVHRR) data. It is based on the physical properties of the AVHRR channels 1–2 reflectance ratios, the brightness temperature differences between channels 4 and 5, and the channel 4 brightness temperatures. In this scheme, clear pixels are first separated from cloudy pixels, which are then classified into three types: cirrus, cirrus/low cloud, and low clouds. The authors have applied this scheme to the satellite data collected over the FIRE II IFO [First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment II intensive field observations area during nine overseas within seven observation dates. Determination of the threshold values used in the detection scheme are based on statistical analysts of these satellite data. The authors have validated the detection results against the cloudy conditions inferred from the collocated and coincident ground-based lidar and radar images, balloonborne replicator data, and National Center for Atmospheric Research CLASS (Cross-chain Loran Atmospheric Sounding System) humidity soundings on a case-by-case basis. In every case, the satellite detection results are consistent with the cloudy conditions inferred from these independent and complementary measurement. The present scheme is well suited for the detection of midlatitude, multilayer cirrus cloud systems and tropical anvils.

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